Data/hora: 03/06/2024 04:31:45

Provedor de dados: 	70	
País: 	Brazil	
Título: 	A SPECTRAL AGROMETEOROLOGICAL MODEL FOR ESTIMATING SOYBEAN GRAIN PRODUCTIVITY IN MATO GROSSO, BRAZIL	
Autores: 	Sarmiento,Christiany M.; Coltri,Priscila P.; Alves,Marcelo de C.; Carvalho,Luiz G. de.	
Data: 	2020-06-01	
Ano: 	2020	
Palavras-chave: 	Geographic Information System; Mathematical Modeling; Remote Sensing; Agrometeorology; Crop Monitoring.	
Resumo: 	ABSTRACT This study used spectral data integrated with the agrometeorological model by Doorenbos and Kassam to estimate soybean grain productivity in the state of Mato Grosso, Brazil. In the developed model, spectral data were used instead of meteorological data and biophysical parameters of the crop. For this purpose, the products of real and potential evapotranspiration (MOD16), normalized difference vegetation index – NDVI (MOD13Q1), and leaf area index (MOD15A2H) from the MODIS satellite were used, in addition to sunstroke data obtained by using the visible channel from the satellite GOES IMAGER. The results obtained showed that, with the proposed methodology, it was possible to follow the development of soybean cultivation throughout the cycle and to estimate production and productivity in the study area. Willmott's agreement index was 0.99 and 0.96 and Pearson's correlation coefficient was 0.99 and 0.84 for production and productivity, respectively.	
Tipo: 	Info:eu-repo/semantics/article	
Idioma: 	Inglês	
Identificador: 	http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162020000300405	
Editor: 	Associação Brasileira de Engenharia Agrícola	
Relação: 	10.1590/1809-4430-eng.agric.v40n3p405-412/2020	
Formato: 	text/html	
Fonte: 	Engenharia Agrícola  v.40 n.3 2020	
Fonte: 	info:eu-repo/semantics/openAccess